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- | ====== Hypergeometric Distribution ====== | ||
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- | In probability theory and statistics, the hypergeometric distribution is a discrete probability distribution that describes the number of successes in a sequence of n draws from a finite population without replacement. | ||
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- | There is a shipment of M objects in which K are defective. The hypergeometric distribution describes the probability that in a sample of n distinctive objects drawn from the shipment exactly x objects are defective. | ||
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- | In general, if a random variable X follows the hypergeometric distribution with parameters M, K and n, then the probability of getting exactly x successes is given by | ||
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- | f(x,M,K,n) = over(K, | ||
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- | where over(n, | ||
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- | The formula can be understood as follows: There are over(M,n) possible samples (without replacement). There are over(K,x) ways to obtain x defective objects and there are over(M-k, | ||
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- | The fact that the sum of the probabilities, | ||
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- | support max(0, | ||
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- | ^Parameter^Description | ||
- | |M |Size of the population | ||
- | |K |Number of items with the desired characteristic in the population|50.0 | ||
- | |n |Number of samples drawn |20.0 | | ||
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